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- Modeling and Simulation of Complex Processes (94) (remove)
cmdtools
(2021)
Molecular dynamics (MD) are extremely complex, yet understanding the slow components of their dynamics is essential to understanding their macroscopic properties. To achieve this, one models the MD as a stochastic process and analyses the dominant eigenfunctions of the associated Fokker–Planck operator, or of closely related transfer operators. So far, the calculation of the discretized operators requires extensive MD simulations. The square-root approximation of the Fokker–Planck equation is a method to calculate transition rates as a ratio of the Boltzmann densities of neighboring grid cells times a flux, and can in principle be calculated without a simulation. In a previous work we still used MD simulations to determine the flux. Here, we propose several methods to calculate the exact or approximate flux for various grid types, and thus estimate the rate matrix without a simulation. Using model potentials we test computational efficiency of the methods, and the accuracy with which they reproduce the dominant eigenfunctions and eigenvalues. For these model potentials, rate matrices with up to $\mathcal{O}\left(1{0}^{6}\right)$ states can be obtained within seconds on a single high-performance compute server if regular grids are used.
This article considers non-stationary incompressible linear fluid equations in a moving domain. We demonstrate the existence and uniqueness of an appropriate weak formulation of the problem by making use of the theory of time-dependent Bochner spaces. It is not possible to directly apply established evolving Hilbert space theory due to the incompressibility constraint. After we have established the well-posedness, we derive and analyse a time discretisation of the system.
We consider linear parabolic equations on a random non-cylindrical domain. Utilizing the domain mapping method, we write the problem as a partial differential equation with random coefficients on a cylindrical deterministic domain. Exploiting the deterministic results concerning equations on non-cylindrical domains, we state the necessary assumptions about the velocity filed and in addition, about the flow transformation that this field generates. In this paper we consider both cases, the uniformly bounded with respect to the sample and log-normal type transformation. In addition, we give an explicit example of a log-normal type transformation and prove that it does not satisfy the uniformly bounded condition. We define a general framework for considering linear parabolic problems on random non-cylindrical domains. As the first example, we consider the heat equation on a random tube domain and prove its well-posedness. Moreover, as the other example we consider the parabolic Stokes equation which illustrates the case when it is not enough just to study the plain-back transformation of the function, but instead to consider for example the Piola type transformation, in order to keep the divergence free property.
Boolean delay equations (BDEs), with their relatively simple and intuitive mode of
modelling, have been used in many research areas including, for example, climate
dynamics and earthquake propagation. Their application to biological systems has been
scarce and limited to the molecular level. Here, we derive and present two BDE models.
One is directly derived from a previously published ordinary differential equation
(ODE) model for the bovine estrous cycle, whereas the second model includes a
modification of a particular biological mechanism. We not only compare the simulation
results from the BDE models with the trajectories of the ODE model, but also validate
the BDE models with two additional numerical experiments. One experiment induces
a switch in the oscillatory pattern upon changes in the model parameters, and the
other simulates the administration of a hormone that is known to shift the estrous
cycle in time. The models presented here are the first BDE models for hormonal
oscillators, and the first BDE models for drug administration. Even though automatic
parameter estimation still remains challenging, our results support the role of BDEs
as a framework for the systematic modelling of complex biological oscillators.
This thesis examines how taking into account surface to surface radiation
impacts the cooling process in general. We formulate the non local bound-
ary condition after introducing the general setting for the cooling model. In
section 3, the mathematical description of the radiative heat transfer is dis-
cussed. We cover the implementation of the radiative matrix in section 4,
which is followed by a brief explanation of the radiative matrix’s structure
and several techniques to dealing with the accompanying challenges.
We investigate the importance of radiative heat transport by applying the
given approach to a two-dimensional geometry and computing the ensuing
cooling curves. We compare the findings of our computation to those ac-
quired from experiment conducted and find that they are extremely similar.
There is a considerable difference (of about 35%) in the time of cooling of the
surface where there is a possibility of influence of radiation from the second
surface to that of the surface with no influence at all. Although it is possible
to infer that heat convection plays a role in the total result, this has yet to be
proved. However, one can clearly see the significance of the surface to surface
radiative heat transfer on these parts confirming the research question posed
at the begining. The effect of the surface to surface radiative heat transfer
has an influence on the resulting cooling time and should be considered in
the model.
In this paper, we explore the relationship patterns between Ancient Egyptian texts of the corpus ``Synodal decrees'', which are originating between 243 and 185 BCE, during the Ptolemaic period. Particularly, we are interested in analyzing the grammatical features of the different texts. Conventional data analysis methods such as correspondence Analysis are very useful to explore the patterns of statistical interdependence between categories of variables. However, it is based on a PCA-like dimension-reduction method and turned out to be unsuitable for our dataset due to the high dimensionality of our data representations. Additionally, the similarity between pairs of texts and pairs of grammatical features is observed through the distance between their representation, but the degree of association between a particular grammatical feature and a text is not. Here, we applied a qualitative Euclidean embedding method that provides a new Euclidean representation of the categories of variables. This new representation of the categories is constructed in such a way that all the patterns of statistical interdependence, similarity, and association, are seen through the Euclidean distance between them. Nevertheless, the PCA-like dimension-reduction method also performed poorly on our new representation. Therefore, we obtained a two-dimensional visualization using non-linear methods such UMAP or t-SNE. Although these dimension-reduction methods reduced the interpretability of interpoint distances, we were still able to identify important similarity patterns between the Synodal text as well as their association patterns with the grammatical features.
The reactivity ratios of acrylic acid (AA, M1) and its dimer beta-acroyloxypropionic acid (diAA, M2) are determined from cumulative copolymerization data by two different methods: classical parameter estimation (PE) by minimizing the objective function and a Bayesian analysis. Classical PE gives r1 =0.74 and r2 = 1.23 at the minimum of the residual. From the Bayesian analysis, the probability distribution of the parameter sets is obtained, revealing the existence of parameter sets with rather the same probability. The influence of the number of data and the size of the measurement error are discussed.